Project 4: Using a prospective cohort survey to test population-level predictions generated by Projects 1-3

项目摘要。烟草产品研究中心(CSTP)开发了一个模型，用于 使用加热液体的电子烟(ECIG)作为样本来评估新型烟草产品 通常含有尼古丁，形成一种气雾剂，使用者可以吸入。现在，CSTP利用其方法和 ECig的专业知识将从产品评估转向影响分析的综合主题。具体地说， CSTP提出了FDA可以对潜在法规的影响进行预测的方法， 然后，可以检验预测的影响是否在人群中发生。CSTP的模式 评估潜在的法规如何影响产品毒性(项目1)、用户行为(项目2)和 产品成瘾/滥用责任(项目3)以及这些项目一起，将有助于预测 人口层面的现象。项目4将测试这些人口水平预测的有效性。 FDA的规定旨在促进健康，但也可能产生意想不到的后果。例如, 将ECIG液体的尼古丁含量限制在20毫克/毫升，就像在欧洲联盟(EU)一样，可以推动高功率ECIG的使用 这会雾化更多的液体，导致使用者吸入更多的尼古丁。也可能发生意想不到的后果 从其他行动，如限制ECIG尼古丁流量(释放尼古丁/单位时间)，或减少味道 可用性。检查这些法规和其他潜在法规如何影响产品毒性、用户行为和 受控环境中的产品滥用责任可能导致对人口水平后果的预测。 然而，这些预测的准确性应该得到检验。烟草产品的人口水平效应 在监管到位后，可以使用大规模纵向调查来衡量监管。项目 4个具体目标是检验由项目1-3的S对照研究得出的总体水平的预测 毒性、用户行为和产品滥用责任使用前瞻性队列调查，包括当前 独家ECIG使用者(N=600)和目前ECIG和烟草香烟的双重使用者(N=600)。具体来说， 这项研究将评估三种可能的监管行动对人口水平的影响：(1)限制尼古丁，(2) 对尼古丁通量的限制，以及(3)风味可利用性的降低。项目4涉及的科学领域是 影响分析及其工具由上下文知识核心提供信息，这将有助于确定 如何在ECIG使用者中准确地评估自我报告和可靠地评估依赖。总体而言，结果将 揭示在受控条件下进行的观察在多大程度上产生有效的总体水平 预测。因此，该项目是一个具有综合影响分析主题的中心的一部分，该主题借鉴了 团队在评估烟草法规对人口水平的影响方面的专业知识，并将为FDA提供一套工具 可以用来指导法规的制定，以便在法规生效时得到验证 人们已经使用各种方法来测试、提炼它，并生成数据表明它的健康促进作用是 最大化和意想不到的后果被最小化。

Project Summary. The Center for the Study of Tobacco Products (CSTP) has developed a model for evaluating novel tobacco products using, as exemplars, electronic cigarettes (ECIGs) that heat a liquid that often contains nicotine, forming an aerosol that users inhale. Now, CSTP leverages its methodological and ECIG expertise to pivot from product evaluation to an integrative theme of impact analysis. Specifically, the CSTP proposes methods with which FDA can generate predictions regarding a potential regulation’s effects, and then whether or not the predicted effects occur in the population can be tested. The CSTP’s model assesses how potential regulation might influence product toxicity (Project 1), user behavior (Project 2), and product addiction/abuse liability (Project 3) and, together, these projects will contribute to predictions regarding population-level phenomena. Project 4 will test the validity of those population-level predictions. FDA regulations are intended to promote health, but also may have unintended consequences. For example, limiting ECIG liquids to <20 mg/ml nicotine, as in the European Union (EU), can drive use of high power ECIGs that aerosolize more liquid, leading users to inhale more nicotine. Unintended consequences may also occur from other action, such as constraining ECIG nicotine flux (emitted nicotine/unit time), or reducing flavor availability. Examining how these and other potential regulations influence product toxicity, user behavior, and product abuse liability in controlled settings can lead to predictions regarding population-level consequences. However, the accuracy of these predictions should be tested. Population-level effects of tobacco product regulation can be measured after the regulation is put into place using large-scale longitudinal surveys. Project 4 specific aims are to test population-level predictions that arise from Project 1-3’s controlled studies of product toxicity, user behavior, and product abuse liability using a prospective cohort survey that includes current exclusive ECIG users (N=600) and current dual users of ECIGs and tobacco cigarettes (N=600). Specifically, the study will assess the population-level effects of three potential regulatory actions: (1) limits on nicotine, (2) constraints on nicotine flux, and (3) reduction in flavor availability. Project 4 addresses the scientific domain of impact analysis and its instruments are informed by the Contextual Knowledge Core that will help determine how to assess self-report accurately and assess dependence reliably among ECIG users. Overall, results will reveal the extent to which observations made under controlled conditions yield valid population-level predictions. Thus, this project is part of a center with an integrative theme of impact analysis that draws on the team’s expertise in evaluating population-level effects of tobacco regulation and will provide FDA a set of tools that can be used to guide regulation development so that, by the time a regulation goes into effect, validated methods have been used to test it, refine it, and generate data that show that its health-promoting effects are maximized and unintended consequences are minimized.